1. Field of the Invention
The present invention relates generally to on-line process control apparatus and methods and more specifically to an on-line control method and apparatus for the predetermined process control of a crystallizer to achieve optimum, desired continuous crystallizer process characteristics.
2. Description of the Prior Art
Various crystallizer apparatus and the associated crystallizer process behavior are discussed in U.S. Pat. Nos. 4,025,307 to A. D. Randolph et al, 3,873,275 to R. C. Bennett and 3,961,904 to R. C. Bennett; "Crystal Size Distribution Dynamics In A Classified Crystallizer: Part I", A. D. Randolph et al, 23 AIChE Journal No. 4 pp. 500-510, July 1977; "Crystal Size Distribution Dynamics in a Classified Crystallizer: Part II", J. R. Beckman et al, 23 AIChe Journal No. 4, pp. 510-520, July 1977; and Theory of Particulate Processes, A. D. Randolph et al, Academic Press, New York, 1971.
As discussed at various portions of the aforementioned prior art, crystal size distribution is an important parameter of an operating crystallizer and much effort has been directed toward reducing crystal size distribution transients and eliminating crystal size distribution instability in industrial crystallizers in order to produce a crystal product within the desired size range and at a desired production rate of efficiency. Extreme crystal size distribution cycling can cause production losses due to off-specification product, overload of associated equipment and equipment fouling. Transients of crystal size distribution are known to be caused by such outside influences to the crystallizer as dilution addition, feed rate, etc . . . while unstable crystal size distributions result from the interaction of system kinetics with the particular crystallizer configuration. Low order cycling of crystal size distribution instability is caused by the fines destruction and classified product removal in a stable low-order region of nucleation vs. supersaturation response.
The arrangements in U.S. Pat. Nos. 3,873,275 and 3,961,904 are directed to regulation of both the size and quantity of crystal fines removed from a slurry body undergoing crystallization.
The AIChE Journal article entitled "Crystal Size Distribution Dynamics In A Classified Crystallizer: Part I" is directed to an experimental and theoretical study of cycling in a potassium chloride crystallizer with simulation of unstable operation with a dynamic model.
The AIChE Journal article entitled "Crystal Size Distribution Dynamics In A Classified Crystallizer: Part II" discusses the simulated control of crystal size distributon for a crystallizer equipped with a fines destruction system and fines removal product classifer. A computer simulator entitled "CYCLER" was developed to simulate the dynamics and control of crystallizers equipped with fines destruction, clear liquor advance, and product classification. The simulator was used extensively throughout the study in the analysis and experimental work and for the development of theoretical control philosphies. A control algorithm was proposed utilizing the fines destruction to product withdrawal ratio as the manipulated variable and the nuclei density as a control variable. A simulation of the control algorithm as a subroutine in the simulation computer was implemented to test the feasibility of the control algorithm and theoretically establish that by controlling nuclei density, crystal size distribution cycling could also be controlled. To verify the computer simulation of the process dynamics of the crystallizer, nuclei densities in the study were obtained from an experimental crystallizer in the laboratory by taking a slurry sample from the fines destruction loops, drying the sample, resuspending the particles in an electrolytic solution, counting the particles with an electronic particle counter, calculating population densities and performing a linear regression analysis on a plot of the log of the population density versus particle size. Nuclei density was then determined as the ordinate intercept of the regressed line. The batch procedure requires a number of hours or days and thus this off-line complicated procedure could not be used to generate data needed for the control of an on-going system.
In U.S. Pat. No. 4,025,307, crystallization properties of human urine in a crystallizer were analyzed to determine renal stone formation characteristics of the sampled humans. A sample output of the crystallizer was analyzed by a particle counter and a computing module to determine the nucleation rate. The nucleation rate was found to be able to distinguish normal urine samples from those from people who were considered renal stone forming candidates. The data from the particle counter provided population density information in various size ranges. A plot of the size ranges and the log of the population density for each size range from the particle counter data were utilized to provide a best-fit line through the calculated data points to provide the nuclei density, nucleation rate and growth rate as determined by the extrapolation of the best-fit line, the slope of the line and the intercept with the log n axis.
While the aforementioned studies and measurement systems are useful in understanding the dynamics and operation of a crystallizer, and generally serve their intended purpose, the prior art fails to provide an on-line control system for the on-line, real-time control of a crystallizer to maintain predetermined operating parameters and to achieve stable predetermined optimum, continuous crystallizer operation for optimum crystal product output or characteristics and to avoid process transients and undesirable cycling behavior.